Antimicrobial Drug Use and Antimicrobial Resistance in Enteric Bacteria Among Cattle from Alberta Feedlots

Abstract

The purpose of this study was to determine whether antimicrobial resistance (AMR) in foodborne pathogens (Escherichia coli O157, Salmonella, and Campylobacter) and non–type-specific E. coli obtained from fecal samples of feedlot cattle was associated with antimicrobial drug (AMD) use. A secondary objective was to determine if AMR in non–type-specific E. coli could be used as a predictor of AMR in foodborne pathogens. Fecal samples were collected from pen floors in 21 Alberta feedlots during March through December 2004, and resistance prevalence was estimated by season (Spring, Fall) and cattle type (fewest days-on-feed and closest to slaughter). AMD exposures were obtained by calculating therapeutic animal daily doses for each drug before sampling from feedlot records. Generalized linear mixed models were used to investigate the relationship between each AMR and AMD use. Non–type-specific E. coli was commonly recovered from fecal samples (88.62%), and the highest prevalence of resistance was found toward tetracycline (53%), streptomycin (28%), and sulfadiazine (48%). Campylobacter jejuni was recovered from 55.3% of the fecal samples, and resistance was generally less for the drugs that were evaluated (doxycycline 38.1%, ciprofloxacin 2.6%, nalidixic acid 1.64%, erythromycin 1.2%). E. coli O157 and Salmonella were recovered much less frequently (7% and 1% prevalence, respectively). The prevalence of recovery for the bacteria studied varied between seasons and cattle types, as did patterns of AMR. Among non–type-specific E. coli, resistance to tetracycline, streptomycin, and sulfadiazine was found to be positively associated with in-feed exposure as well as injectable tetracycline, but these differences were relatively small and of questionable practical relevance. Among C. jejuni isolates, cattle type was significantly associated with doxycycline resistance. Results suggested that resistance in non–type-specific E. coli to chloramphenicol, trimethoprim/sulfamethoxazole, and tetracycline might be used as predictors of resistance to these drugs in E. coli O157 recovered from the same fecal samples.

Introduction

A ntimicrobial resistance (AMR) among bacteria is a growing global concern for human and animal health. It is a complex issue that should not be oversimplified or overgeneralized because there is not a simple, direct relationship between antimicrobial drug (AMD) use and AMR (USDA, 1999b). There is a concern that AMD use in food animals can lead to the selection of resistant enteric bacteria that may eventually be transferred to people by the consumption of contaminated food or through direct animal contact or environmental exposure (USDA, 1999b). Conscientious use of AMDs is among the first-line control measures that are recommended for combating AMR in feedlots. However, it remains unproven that increased use of AMDs in feedlot cattle creates meaningful increases in resistance among pathogenic or nonpathogenic bacteria recovered from these animals, or that such increased resistance increases health risks for humans.

Based on the studies conducted by the U.S. Department of Agriculture's National Animal Health Monitoring System between 1990 and 1997 in the United States, approximately 25% of the small cattle feedlot operations (feedlots with 1000 to 7999 head count) and 70% of the large feedlot operations (greater than 8000 head count) used antimicrobials at some time during the feeding period (USDA, 1999a, edited 2007). AMDs are administered to cattle in feedlots for a variety of reasons, including prevention or treatment of disease in individuals and groups, control of liver abscesses, promotion of more efficient feed conversion, and acceleration of weight gain. Respiratory disease complex (e.g., pneumonia) is a major feedlot health problem and an important determinant of antimicrobial use (USDA, 1999b). Pneumonia and neonatal diarrhea are major causes of calfhood mortality, and calves are often treated individually by injection or in groups through feed, water, or by injection (USDA, 1997; McEwen and Fedorka-Cray, 2002).

This study was designed to investigate associations between AMD use in feedlots and occurrence of AMR in enteric bacteria obtained from feces of cattle. This study also investigated whether AMR in non–type-specific Escherichia coli was predictive of AMR in foodborne pathogens recovered from the same samples (E. coli O157, Campylobacter jejuni, or Salmonella enterica).

Materials and Methods

Study population and sample collection

Twenty-one feedlots in Alberta with greater than 5000 head capacity were randomly selected for participation in the study (Van Donkersgoed et al., 2009). Cattle were managed in these facilities using standard industry practices.

Briefly, cattle were purchased from a variety of sources, including individual ranches and livestock auction markets. Upon arrival, cattle were commonly treated with antihelmintic drugs, implanted with growth hormones, and vaccinated against respiratory disease agents and clostridial agents. If individuals or groups were considered to be high risk for respiratory disease, they were treated with injectable AMDs as a prophylactic/metaphylactic disease control measure. Incoming groups of cattle were assigned to specific pens for housing, and these cohorts generally remained together throughout the feeding period. Assignment to pens (i.e., physical location) was made irrespective of the disease history and management strategies employed with cattle that had previously been housed in the same pens. Thus, while not documented, cattle could have been housed in pens that previously housed cattle with a variety of AMD exposures and disease histories. All cattle were fed nutritionally balanced rations throughout the feeding periods. Trained feedlot personnel observed cattle in all pens on a daily basis to identify animals that looked abnormal. These abnormal cattle were moved from their pen to a hospital facility where trained personnel worked under the direction of feedlot veterinarians to examine the animals and diagnose their condition. Cattle thought to be clinically sick from conditions due to bacterial infections were treated with therapeutic doses of AMDs in accordance with treatment protocols prescribed by supervising veterinarians. Producers documented cattle treatment information using a variety of methods ranging from computerized animal health databases to paper records, and the amount of information recorded varied among feedlots. Many feedlots maintained very detailed individual treatment records and recorded information such as the date treated, unique animal identification, animal weight, diagnosis, drug, dose, route of injection, location of injection, person pulled animal, person treating animal, animal pen movements, and drug meat withdrawal. A few operations only recorded the number of animals that received a particular drug.

To obtain fecal samples used in this study, each feedlot was visited once in the Spring and once in the Fall during 2004 as previously described (Van Donkersgoed et al., 2009). Briefly, at each visit, two types of cattle were randomly identified for sampling: one was the type of cattle (pen) that had most recently arrived at the feedlot (newly arrived) and the other type was identified from all the pens that were within 2 weeks of slaughter (preslaughter). A total of 84 pens were sampled for this project. Twenty-five fresh manure samples (25–50 g) were collected from the floor of these selected pens in a representative systematic manner. The samples were placed on ice packs and sent by overnight courier to the laboratories where they were cultured to isolate E. coli O157, Salmonella enterica, C. jejuni, and non–type-specific E. coli. Non–type-specific E. coli, E. coli O157, Salmonella, and Campylobacter were isolated as previously described (Van Donkersgoed et al., 2009).

Antimicrobial susceptibility testing

The susceptibility of all non–type-specific E. coli isolates was characterized by agar dilution breakpoint assays according to the CLSI (2002) guidelines. The antimicrobials tested included amikacin, amoxicillin/clavulanic acid, ampicillin, ceftiofur, cephalothin, chloramphenicol, gentamicin, nalidixic acid, streptomycin, sulfadiazine, sulfamethoxa-zole/trimethoprim, and tetracycline. All Campylobacter isolates were screened for resistance using agar dilution methods with breakpoint concentrations of ciprofloxacin, doxycycline, erythromycin, and nalidixic acid (Ge et al., 2002). The control strain C. jejuni ATCC 33560 was included on each agar dilution plate. E. coli O157 and Salmonella enterica were tested for antimicrobial susceptibility by a broth microdilution method (Sensititer^®, Trek Diagnostic Systems, West Sussex, UK) according to the manufacturer's instructions, using E. coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, Enterococcus faecalis ATCC 29212, and Staphylococcus aureus ATCC 29213 as controls.

Exposure to AMDs

Individual and mass antimicrobial treatment information was retrieved from records obtained from the 21 feedlots enrolled in this study. A standard data capture form was used to collect information from the feedlots on feed medications and processing procedures. Copies of existing feedlot treatment records were requested for those pens sampled. The amount of each drug administered to cattle was converted into standardized animal daily doses (ADDs) according to the licensing information regarding recommended doses needed to provide therapeutic efficacy for the treatment of respiratory disease in feedlot cattle (Animal drugs at Food and Drug Administration: www.accessdata.fda.gov/scripts/animaldrugsatfda/). Even though AMDs were sometimes administered for other purposes (e.g., in-feed medication for liver abscess control), all ADDs were converted to ADDs that were relevant to the treatment of respiratory disease. The AMD exposures (both in-feed and as injectables) used in analyses were summarized at the group level as the total number of ADDs administered to a group of cattle before the sampling date. The ADDs for individual drugs were summed within drug classes or subclasses (penicillins, cephalosporins, phenicols, fluoroquinolones, macrolides, sulfonamides, and tetracyclines). There was no reported administration of drugs via drinking water at any of the feedlots. The therapeutic duration of a single administration of long-acting tetracyclines, macrolides, fluoroquinolones, phenicols, and long-acting penicillins was considered to be 3 days per administration as per label recommendations for dosing (Animal drugs at Food and Drug Administration). For estimating the number of ADDs associated with in-feed medication, all cattle were assumed to have an average body weight of 800 lbs; animals were arbitrarily assumed, based on the experience with feeding cattle, to have uniformly consumed feed at the rate of 2.5% of its body weight per day, and the supplements were assumed to have been added to the rations at 3% of the total feed weight on a dry matter basis (unless otherwise specified in the treatment records).

Statistical analysis

Data were entered into computer databases (Microsoft^® Excel) and validated by comparison to paper records. Data were evaluated graphically and by calculating unadjusted descriptive statistics (SAS v9.1; SAS Institute, Cary, NC). All analyses regarding AMD exposures were performed by summarizing observations at the pen level. The average number of animals in each pen type was calculated and compared. Drug exposures were standardized by dividing pen-level exposures by the number of animals in the pen and the amount of time cattle had been at risk of exposure before sampling, yielding estimates of ADDs per head per day. Regression analysis using generalized estimating equations (PROC GENMOD, SAS v9.1; SAS Institute) with normal distribution function was used to compare the ADD exposures (penicillins, cephalosporins, phenicols, fluoroquinolones, macrolides, sulfonamides, and tetracyclines) across sampling seasons (Spring, Fall) and type of animals/pens (newly arrived, preslaughter). To facilitate the analysis of antimicrobial susceptibility, bacteria were categorized as resistant (included resistant and intermediates) or susceptible. Regression analysis using generalized estimating equations (PROC GENMOD, SAS v9.1; SAS Institute) with a binomial distribution function was used to evaluate whether season and type of cattle were associated with difference in the likelihood of resistance in bacteria. The pens of newly arrived animals sampled during Spring season were considered as the reference group to compare other categories of animal/pen type and season.

Poisson regression was used to investigate associations between AMD exposure in pens and the occurrence of AMR at the group level. Counts of bacteria with AMR were the outcome for these models, and drug exposure information (ADDs per head per day) was the primary exposure variable of interest for these models. A separate model was constructed to investigate the influence of AMD use on susceptibility to each AMD that was evaluated. Although each drug resistance was analyzed in a different model, drug exposures for all classes of drugs were evaluated in all models as potential determinants of the likelihood of resistance. In-feed and injectable drugs were analyzed as separate exposure variables in the models. Random intercept mixed effect models (generalized linear mixed model regression) were used to control for the lack of independence in observations due to the collection of multiple fecal samples from each pen (PROC GLIMMIX SAS v9.1; SAS Institute). Isolates were identified in models as repeated observations nested within the feedlots, and feedlots were modeled as a random effect. Season (Spring/Fall) and type of cattle (newly arrived/preslaughter) were analyzed as fixed effects. Exposure estimates for all drug classes were entered into all initial models, and backward elimination was used to determine which variables were retained in final models. Season (Spring/Fall) and type of cattle (newly arrived/preslaughter) were controlled in all models as potential confounding variables. The critical alpha for comparisons was set at 0.05. When inclusion of variables in models created model instability (as evidenced by extremely high parameter estimates and extremely wide confidence intervals [CIs]), these variables were removed from models, and the model selection process continued until a stable model was obtained. Adjusted baseline resistance prevalence estimates were obtained from model intercepts, and effects of AMD exposure were assessed by calculating adjusted risk estimates using parameter estimates and standard error (SE) estimates obtained from the variance–covariance matrix.

To provide a practically relevant measure of effect from these analyses regarding injectable drugs, adjusted risk (probability) estimates for the occurrence were calculated for relative to AMD exposures that might be experienced by cattle groups with low or high risk of respiratory disease. Cattle from groups with a low theoretical risk of respiratory disease were assumed to have not received AMDs upon arrival for prophylaxis/metaphylaxis and assumed to have approximately 0.5% crude mortality for the feeding period, with an accompanying 1% overall morbidity rate for diseases requiring injectable AMD treatment rate, that 25% of these requiring a second treatment (first relapse), and that 25% of the animals that were treated twice would require a third treatment (second relapse). Cattle in groups with a high theoretical risk of respiratory disease were assumed to have approximately 4% crude mortality rate for the feeding period. It was also assumed that all high-risk cattle would receive an injectable AMD as prophylaxis/metaphylaxis for respiratory disease, that there would be a 15% crude morbidity rate for diseases requiring initial injectable treatment, that 25% would experience a first relapse, and 25% would experience a second relapse. Mortality, morbidity, and associated treatment rates used in these assumptions were extrapolated from previously published literature (Perrett et al., 2008). All of these injectable treatments were assumed to be with a long-acting AMD and that each treatment would therefore attribute three ADDs.

To evaluate the AMR among non–type-specific E. coli as a predictor of AMR in other bacteria within the same sample, logistic regression models using generalized estimating equations (PROC GENMOD, SAS v9.1; SAS Institute) were constructed to separately compare resistance to each AMD. Resistance (yes/no) among non–type-specific E. coli to a drug (chloramphenicol, sulfisoxazole, tetracycline, trimethoprim/sulfamethoxazole, nalidixic acid) was included as an independent predictor variable for resistance (yes/no) in a foodborne pathogen species. The antimicrobials that were evaluated in both non–type-specific E. coli and the other bacteria in question were used in these models. A separate analysis was performed to evaluate the association between doxycycline resistance in Campylobacter and the resistance to tetracycline in non–type-specific E. coli. The analyses were performed at the level of the isolate.

Results

Samples were collected from a total of 84 pens distributed among the 21 participating feedlots. The mean numbers of animals housed in newly arrived pens (mean = 191, standard deviation [SD] = 90) and preslaughter pens (mean = 171, SD = 90) were significantly smaller in the Fall season (p < 0.0001) when compared with the newly arrived animals in the Spring season. The mean number of animals in newly arrived (mean = 220, SD = 110) and preslaughter (mean =208, SD = 90) pens sampled in the Spring were not significantly different (p = 0.62). The median number of days-on-feed was 198 and 160 for preslaughter pens sampled in the Spring and Fall, respectively, and the median number of days-on-feed for newly arrived pens was 15 and 12, respectively.

Exposure to AMDs

Overall, differences in ADD exposures were significant between season and type of animals (Tables 1 and 2). As expected, the in-feed exposures to sulfonamides and macrolides were greater in preslaughter animals during both seasons when compared with the estimates for newly arrived cattle (Table 1). However, the average in-feed exposure to tetracycline was lower in preslaughter animals during both seasons compared with the exposures accumulated by the newly arrived animals sampled during the Spring (Table 1). In contrast, AMD exposures for newly arrived pens of cattle were greater for cattle sampled in the Fall when compared with the similar groups sampled during the Spring (Table 1). Average exposures to injectable AMDs were greatest for tetracycline and florfenicol, followed at some distance by exposures to macrolides (Table 2). However, average rates of exposure varied considerably among drug classes by season and type of cattle group (Table 2).

Table 1.

In-Feed Administration of Antimicrobial Drugs to Cattle Groups Before Sampling (per 1000 Head per Day)

		Sulfonamides			Macrolides			Tetracyclines
		ADDs			ADDs			ADDs
Season	Type of group	Mean	SD	p-Value	Mean	SD	p-Value	Mean	SD	p-Value
Spring	Shortest on feed	0	0	Reference	14	50	Reference	1437.2	2261.3	Reference
Spring	Preslaughter	42.8	94.9	<0.0001	205.2	493.1	<0.0001	657.3	1301.9	<0.0001
Fall	Shortest on feed	0	0	1	0.19	0.7	0.57	3398.6	4586.7	<0.0001
Fall	Preslaughter	13.5	52.4	0.0003	167.8	340.3	<0.0001	998.5	1742.2	0.01

p-Values were obtained from generalized estimating equations (PROC GENMOD, SAS v9.1; SAS Institute) with normal distribution function to compare the ADD exposures across sampling seasons and groups of animals. Sulfonamide class of antimicrobial in feed included sulfamethazine; macrolide class included tylosin; tetracycline class included tetracyline. ADDs, animal daily doses, SD, standard deviation.

Table 2.

Injectable Antimicrobial Drugs Administered to Cattle Before Sampling (per 1000 Head per Day)

		Penicillins			Cephalosporins			Phenicols			Fluoroquinolones
		ADDs			ADDs			ADDs			ADDs
Season	Pen type	Mean	SD	p-Value	Mean	SD	p-Value	Mean	SD	p-Value	Mean	SD	p-Value
Spring	SOF	0.05	0.2	Reference	0.1	0.4	Reference	16.5	52.5	Reference	0	0	Reference
Spring	PS	0.2	0.4	0.02	0.4	0.6	<0.0001	2.2	5.8	<0.0001	0	0	1
Fall	SOF	0	0	0.01	0.3	0.6	<0.0001	15.2	35.5	0.1	0.3	0.98	<0.0001
Fall	PS	0.1	0.3	<0.0001	0.3	0.4	<0.0001	0.5	1.5	<0.0001	0.002	0.01	0.9

		Macrolides			Sulfonamides			Tetracyclines
		ADDs			ADDs			ADDs
Season	Pen type	Mean	SD	p-Value	Mean	SD	p-Value	Mean	SD	p-Value
Spring	SOF	0.8	1.5	Reference	0.2	0.5	Reference	29.0	106.9	Reference
Spring	PS	1.7	3.4	0.02	0.3	0.7	0.0005	7.0	11.2	<0.0001
Fall	SOF	3.4	8.6	<0.0001	0.1	0.3	0.0004	122.9	164.7	<0.0001
Fall	PS	0.06	0.1	0.02	0.2	0.3	0.02	3.1	6.0	<0.0001

“Season” indicates two sampling periods in 2004 (March to July—designated as Spring—and September to December—designated as Fall). “Pen type” indicates two groups of cattle (pen): one that had most recently arrived at the feedlot (shortest on feed/newly arrived) and the other group were within 2 weeks of slaughter (preslaughter). p-Values were obtained from generalized estimating equations (PROC GENMOD, SAS v9.1; SAS Institute) with normal distribution function to compare the ADD exposures across sampling seasons and groups of animals. Penicillin class of injectable antimicrobial included penicillin, long-acting penicillin, and procaine penicillin; cephalosporins included ceftiofur sodium; phenicols included florfenicol; fluoroquinolones included enrofloxacin; macrolides included tilmicosin; sulfonamides included trimethoprim/sulfadoxine; tetracycline class included biomycin, chlortetracycline, liquamycin, oxytetracyline, long-acting oxymsycine, and tetracycline.

Recovery of bacteria and AMR patterns

AMR in non–type-specific E. coli

Non–type-specific E. coli was recovered from 88.6% of fecal samples during the study (Table 3); thus, 1861 isolates were available for analysis (26.0% from newly arrived pens and 25.9% from preslaughter pens both sampled in the Fall; 23.8% from newly arrived pens and, 24.3% from preslaughter pens both sampled in the Spring). However, among all 84 pens sampled, antimicrobial use data were available for only 75 pens.

Table 3.

Unadjusted Prevalence (%) of Antimicrobial Resistance Among Non–Type-Specific Escherichia coli Recovered from the Feces of Feedlot Cattle

		Spring		Fall
Antimicrobial (%)		Newly arrived n = 443	Preslaughter n = 454	Newly arrived n = 483	Preslaughter n = 481
Amikacin	% Prevalence	0	0	0	0
	95% CI	0	0	0	0
Ampicillin	% Prevalence	6.3	2.4^a	6.6	4.6
	95% CI	4.32–9.11	1.28–4.42	4.64–9.32	2.96–6.95
Amoxicillin–clavulanate	% Prevalence	13.8	11.0	0.4^a	0.4^a
	95% CI	10.77–17.41	8.36–14.35	0.072–1.66	0.072–1.66
Ceftiofur	% Prevalence	0	0.7^b	0.8^b	0.6^b
	95% CI	0	0.17–2.09	0.27–2.26	0.16–1.97
Cephalothin	% Prevalence	14.2	11.9	5.2^a	5.4^a
	95% CI	11.17–17.9	9.13–15.32	3.45–7.65	3.63–7.92
Chloramphenicol	% Prevalence	3.2	2.6	6.2^b	1.0^a
	95% CI	1.81–5.37	1.44–4.7	4.3–8.85	0.38–2.55
Gentamicin	% Prevalence	0	0	0.2	0
	95% CI	0	0	0.011–1.33	0
Nalidixic acid	% Prevalence	0.5	0.2	0.4	0.6
	95% CI	0.078–1.8	0.012–1.42	0.072–1.66	0.16–1.97
Streptomycin	% Prevalence	35.7	39.2	19.9^a	19.3^a
	95% CI	31.24–40.35	34.72–43.88	16.46–23.78	15.96–23.21
Sulfadiazine	% Prevalence	86.7	83.3	19.0^a	10.8^a
	95% CI	83.08–89.63	79.43–86.51	15.7–22.9	8.25–14.02
Tetracycline	% Prevalence	51.5	57.5	45.8	55.3
	95% CI	46.71–56.2	52.79–62.06	41.26–50.32	50.73–59.79
Trimethoprim–sulfamethoxazole	% Prevalence	1.8	0.4	3.7	1.2
	95% CI	0.84–3.67	0.076–1.76	2.29–5.94	0.51–2.83

Significance was based on generalized estimating equations (PROC GENMOD, SAS v9.1; SAS Institute) with a binomial distribution function to evaluate whether season and type of cattle were associated with difference in the likelihood of resistance in bacteria.

Significantly lower than Spring newly arrived.

Significantly higher than Spring newly arrived.

CI, confidence interval.

Among 1861 non–type-specific E. coli isolates, 74.4% showed resistance to at least one AMD (most commonly to tetracycline), 45.1% were resistant to at least two drugs, and 24.1% to at least three drugs (Table 3). Overall, the highest resistance prevalence among season and pen type classifications was seen for sulfadiazine during the Spring (>80% of isolates), followed by tetracycline resistance (45–48%), which was similar across all of these categories (Table 3). In fact, tetracycline resistance was the only resistance that did not vary in prevalence among season and pen types. Resistance among non–type-specific E. coli to amoxicillin/clauvulanic acid, cephalothin, streptomycin, and sulfadiazine was significantly less frequent among isolates recovered from newly arrived and preslaughter cattle during the Fall season when compared with the newly arrived animals during the Spring season (Table 3). Resistance to chloramphenicol was significantly higher among isolates recovered from newly arrived cattle and lower in those recovered from preslaughter cattle in the Fall when compared with the newly arrived animals sampled in the Spring; isolates recovered from preslaughter animals sampled in the Spring were not different from the reference group. Resistance to ampicillin was lowest among isolates from preslaughter animals in the Spring. Resistance to ceftiofur was rare, but compared with the isolates recovered from newly arrived cattle in the Spring, resistance was significantly higher among isolates recovered from the other groups. Nalidixic acid and trimethoprim/sulfamethoxazole resistance was quite rare and not significantly different among different groups of cattle (Table 3).

AMR in E. coli O157

E. coli O157 was isolated from 148 fecal samples, representing 7.1% of the total samples. The majority of isolates (54.7%) were recovered in the Fall from newly arrived animals. In general, resistance was less common among E. coli O157 isolates compared with the non–type-specific E. coli isolates. Sixteen percent of the 148 samples showed resistance to at least two AMDs, 3% were resistant to three AMDs, and 2% to four drugs. Resistance to sulfisoxazole and tetracycline was identified in samples recovered from newly arrived and preslaughter animals in both sampling seasons. Resistance to each of the two drugs was less common during Spring (5.9%) and Fall (8%) in preslaughter and fall newly arrived animals (14.8%) when compared with newly arrived animals during Spring (36%). Resistance to chloramphenicol was highest in isolates obtained from newly arrived animals during the Spring (12%) and moderate in isolates obtained from cattle sampled in the Fall (3.7%). Resistance to trimethoprim/sulfamethoxazole (12%) was detected among isolates recovered from the newly arrived cattle sampled in the Spring animals but not detected in isolates recovered from other cattle.

AMR in Salmonella

Salmonella enterica representing a variety of serotypes (Rubislaw, Saintpaul, Enteritidis, Mbandaka, 4,5,12:i:- and Typhimurium) were isolated from only 0.95% of the fecal samples (n = 20). Twenty-five percent of the isolates represented serotype Saintpaul that exhibited a common pentadrug resistance pattern (ampicillin, chloramphenicol, streptomycin, sulfisoxazole, and tetracycline) in addition to amoxicillin–clavulanate, cefoxitin, and ceftiofur resistance. Five percent (n = 1) of the isolates represented serotype Mbandaka and another 5% (n = 1) represented serotype 4,5,12:i:-, both showed pentadrug resistance pattern in addition to amoxicillin–clavulanate resistance. Another 5% (n = 1) of the isolates belonged to serotype Typhimurium that showed pentadrug resistance in addition to kanamycin and trimethoprim–sulfamethoxazole resistance.

AMR in Campylobacter

A total of 1183 Campylobacter isolates were isolated; 98.2% (n = 1162) were C. jejuni and 1.8% (n = 21) were Campylobacter coli. Seventy-one percent (15 out of 21) of the C. coli isolates showed resistance to doxycycline. However, C. coli were excluded from further analysis because there were so few isolates. Overall, C. jejuni were isolated from 55.3% of the fecal samples collected. About 38% were resistant to at least one AMD, 2% to two AMDs, and 0.8% to three AMDs (Table 4). In general, there was moderate resistance to doxycycline, and resistance to other drugs was rare. Resistance to doxycycline was highest among isolates recovered from preslaughter animals (sampled from both seasons) when compared with the isolates from the newly arrived animals (Table 4).

Table 4.

Unadjusted Prevalence (%) of Antimicrobial Resistance in Campylobacter Jejuni in the Manure of Feedlot Cattle by Sampling Season and Type of Cattle

		Spring		Fall
Antimicrobial (%)		Newly arrived n = 220	Preslaughter n = 309	Newly arrived n = 206	Preslaughter n = 427
Ciprofloxacin	% Prevalence	1.4	1.9	6.3^a	1.9
	95% CI	0–2.9	0.4–3.5	3.0–9.7	0.6–3.2
Doxycycline	% Prevalence	27.7	42.1^a	25.7	46.6^a
	95% CI	21.8–33.7	36.5–47.6	19.7–31.7	41.9–51.4
Erythromycin	% Prevalence	0.5	1.9	3.4	0
	95% CI	0–1.4	0.4–3.5	0.9–5.9	0
Nalidixic Acid	% Prevalence	0.5	1.3	3.9^a	1.4
	95% CI	0–1.4	0.03–2.6	1.2–6.5	0.3–2.5

Significantly higher than isolates recovered from the newly arrived cattle sampled in the Spring.

Associations between AMD use and AMR

Non–type-specific E. coli

In-feed medication with tetracyclines was found to be significantly associated with resistance among non–type-specific E. coli to three drugs (streptomycin, sulfadiazine, and tetracycline) (Table 5). Comparing estimates for cattle that did not receive any in-feed tetracycline treatment to estimates for groups in which every animal received one therapeutic ADD (resistance prevalence in cattle with AMD exposure in Table 5) of tetracycline in-feed every day before sampling, the predicted differences in resistance prevalence were modest (1.9%, 6.0%, and 1.95% absolute differences for resistance to streptomycin, sulfadiazine, and tetracycline, respectively; Table 5). Comparing untreated cattle to groups of cattle with an assumed low-risk AMD exposure, the differences in resistance prevalence were either absent or quite small (0.0%, 0.01%, and 0.01% absolute differences for resistance to streptomycin, sulfadiazine, and tetracycline, respectively). In-feed medication with macrolides (i.e., tylosan) was not associated with any detectable differences in resistance prevalence among non–type-specific E. coli. For injectable AMDs, only exposure to tetracycline injections was associated with differences in AMR; injectable tetracycline exposure was associated with detectable differences in resistance to streptomycin, sulfadiazine, and tetracycline (Table 5). However, comparing untreated cattle to groups of cattle with an assumed low-risk AMD exposure, the differences in resistance prevalence were quite small (0.01%, 0.02%, and 0.01% absolute differences for resistance to streptomycin, sulfadiazine, and tetracycline, respectively; Table 5). Comparing untreated cattle to groups of cattle with an assumed high-risk AMD exposure, the differences in resistance prevalence were small also (0.87%, 2.16%, and 0.68% absolute differences for resistance to streptomycin, sulfadiazine, and tetracycline, respectively; Table 5). Although the variable “type of cattle” (newly arrived/preslaughter) was included in all models, it was only found to be significantly associated with differences in tetracycline resistance prevalence; adjusting for other variables in the model, the average resistance prevalence was lower in isolates obtained from cattle in newly arrived pens (46%, 95% CI = 32.6–52.8%) than in isolates obtained from cattle in preslaughter pens (54%, 95% CI = 53.5–63.3%).

Table 5.

Prevalence Estimates for Antimicrobial Resistance Predicted from Multivariable Models Relative to Varying Levels of Exposures to Drugs That Were Significantly Associated with Differences in Antimicrobial Resistance Among Non–Type-Specific Escherichia coli Recovered from the Feces of Feedlot Cattle

Antimicrobial drug exposure	Resistance	Unexposed (%)	95% CI	Low exposure (%)	95% CI	High exposure (%)	95% CI
In-feed^a	STR	28.20	21.9–36.3	28.20	21.91–36.3	30.11	22.5–40.3
Tetracycline	SUL	74.10	63.0–87.1	74.11	63.05–87.12	80.15	65.9–97.5
	TET	43.50	34.9–54.2	43.51	34.93–54.2	45.46	35.5–58.3
	STR	28.20	21.9–36.3	28.21	21.9–36.3	29.07	22.2–38.1
Injectable^b	SUL	74.11	63.1–87.1	74.13	63.1–87.2	76.27	64.0–91.0
Tetracycline	TET	43.51	34.9–54.2	43.52	34.9–54.2	44.19	35.0–55.8

Assuming one therapeutic ADD was administered in feed per head on every day before sampling.

Theoretically unexposed groups were assumed to have no morbidity requiring parenteral treatment. Estimates for low exposures to injectable drugs were based on an assumption that 1% of the group received an initial injectable treatment, 25% of these received a second treatement (first relapse), and 25% of those received a third treatment (second relapse) with no metaphylaxis. Estimates for high-risk exposures were based on the assumption that 100% of the group received metaphylactic treatment at arrival, 15% received an initial injectable treatment, 25% of these received a second treatment (first relapse), and 25% of those received a third treatment (second relapse). All injectable treatments were assumed to be with long-acting drugs that had three ADDs per treatment.

STR, streptomycin; SUL, sulfisoxazole; TET, tetracycline.

Campylobacter

Exposure to AMDs was not associated with detectable differences in resistance among C. jejuni isolates. Although there was a detectable difference among C. jejuni in doxycycline resistance relative to the type of cattle and season (Table 4) that were sampled, this difference was small and of questionable practical relevance: isolates obtained from newly arrived cattle had an average resistance prevalence of 21.1% (95% CI = 14.0–31.7%) compared with the isolates from preslaughter cattle, which had an average resistance prevalence of 21.4% (95% CI = 11.8–38.9%).

AMR in non–type-specific E. coli as a predictor to determine AMR in other bacteria

Only predictors for chloramphenicol, streptomycin, sulfisoxazole, tetracycline, and trimethoprim/sulfamethoxazole could be analyzed because of the lack of detected resistance to other drugs among E. coli O157. Similarly, only nalidixic acid resistance was analyzed regarding predictors for Campylobacter phenotype as this was the only drug resistance evaluated in both non–type-specific E. coli and Campylobacter. The odds ratios (ORs) suggested that resistance to chloramphenicol, trimethoprim/sulfamethoxazole, and tetracycline in non–type-specific E. coli could be predictors for resistance to the same drugs among E. coli O157 recovered from the same fecal samples (respectively, OR = 22.6, 95% CI = 1.2–416.1; OR = 57.5, 95% CI = 4.3–773.6; OR = 4.5, 95% CI = 1.2–16.1) (Table 6). Models for sulfisoxazole and streptomycin were not significant. Resistance to nalidixic acid among non–type-specific E. coli was not significantly associated with resistance in Campylobacter. However, resistance to tetracycline in non–type-specific E. coli was significantly associated with the resistance to doxycycline in Campylobacter (OR = 1.6, 95% CI = 1.1–2.3). Predictors of resistance in Salmonella were not analyzed because of the low numbers of Salmonella isolates (n = 20).

Table 6.

Antimicrobial Resistance in Non–Type-Specific Escherichia coli as a Predictor of Antimicrobial Resistance in Escherichia coli O157 in the Manure of Feedlot Cattle

		CHL	FIS	TET	SXT
E. coli O157	p-Value	0.036	0.22	0.023	0.002
	OR	22.6	2.06	4.45	57.5
	95% CI	1.23–416.07	0.64–6.62	1.23–16.07	4.27–773.56

OR, odds ratio; CHL, chloramphenicol; FIS, sulfisoxazole; TET, tetracycline; SXT, trimethoprim/sulfamethoxazole.

Discussion

This study showed that the prevalence of recovery for the bacteria varied between seasons and among the cattle types, as did patterns of AMR (Van Donkersgoed et al., 2009). There were some significant associations detected among the AMD exposures and AMR in bacteria. Although some associations were identified, the size of the effect was moderate for in-feed exposures and small for injectable drugs. Further, the significance of these differences relative to animal or public health is not clear. For example, although resistance among non–type-specific E. coli isolates was most commonly detected against tetracycline and in-feed exposure was associated with a 2% difference in the resistance prevalence between the two groups (nonexposed vs. exposed tetracycline in-feed group), this class of drugs continues to be efficacious and useful for a variety of purposes in feedlot cattle, including treatment of respiratory disease (O'Connor et al., 2002), control of liver abscesses, and growth promotion (McEwen and Fedorka-Cray, 2002; Schunicht 2002a, 2002b). Tetracycline treatment was also associated with tetracycline and sulfizoxazole resistance. It was interesting that resistance to streptomycin, sulfisoxazole, and tetracycline was associated with both in-feed and injectable treatment with tetracycline, which also had the highest prevalence of resistance among non–type-specific E. coli, which may suggest that a co-selection method was responsible.

Other studies in feedlot cattle have identified varied responses between AMR and AMD exposures. Studies on fecal non–type-specific E. coli have suggested that a single administration of the long-acting medications can have detectable, short-term impacts on the prevalence of resistant isolates, but that measureable differences between treated and untreated cattle disappear after a short period of time (Stabler et al., 1982; Berge et al., 2005; Lowrance et al., 2007). A study in feedlot steers in Canada that received subtherapeutic levels of tetracycline in combination with sulfamethazine showed an increased prevalence of tetracycline- and ampicillin-resistant E. coli (Alexander et al., 2008). In contrast, another study conducted in a western Canadian feedlot found no associations between antimicrobial use and AMR (Checkley et al., 2008). Another study in feedlot cattle found an association between injectable oxytetracycline and an increase in the prevalence of resistance to sulfisoxazole and chloramphenicol among E. coli beyond those due to the in-feed chlortetracycline, and these changes were detectable a substantial time after treatment with injectable oxytetracycline (O'Connor et al., 2002). The reason proposed was that the in-feed chlortetracycline increased the level of resistance to tetracycline to “saturation,” and therefore injectable oxytetracycline could have no detectable additional impact on the prevalence of resistance. Thus, further work is needed to clarify whether these differences are consistently found in other feedlot populations and whether they are associated with significant health risks to cattle or people.

Resistance to certain drugs in non–type-specific E. coli and C. jejuni was more prevalent during the Fall season in the newly arrived animals compared to other groups. This difference may have occurred because fall placed calves are the highest risk cattle for bovine respiratory disease and generally tend to be treated more commonly than backgrounded Spring placed calves. However, it is possible that this association is specific to some unique aspect of this dataset rather than being a common finding relative to all feedlot cattle in Alberta. The findings of AMR in C. jejuni showed high resistance to doxycycline (belonging to tetracycline group) and low resistance to erythromycin, ciprofloxacin, and nalidixic acid. Similar observations were made in a study in Canada which showed that antimicrobial administration to beef cattle selects for AMR campylobacters, developing substantial resistance to tetracycline and only limited resistance to erythromycin, ampicillin, and ciprofloxacin (Inglis et al., 2005).

When investigating the use of AMR in E. coli as a predictor of resistance in other bacteria, strong associations were found between resistance in non–type-specific E. coli and resistance in E. coli O157 for chloramphenicol, trimethoprim/sulfamethoxazole, and tetracycline. A strong association was also detected between the resistance to tetracycline in non–type-specific E. coli and resistance to doxycycline in Campylobacter; both of these drugs belong to the same antimicrobial class. These findings may have useful implications, but further work is needed to corroborate these findings, especially given the relatively rare isolation of E. coli O157.

Conclusions

Although there were some associations detected between the in-feed exposure of AMD and AMR in these feedlots in this study, differences associated with treatment were small and of unknown relevance. More such in-depth studies would be helpful in answering questions on drug use in cattle and the development of AMR in cattle, as well as what risk this poses to animal and human health.

Footnotes

Acknowledgments

We would like to thank the 21 Alberta feedlot producers who participated in this study. We are grateful to the technical support by Robin Downen, Darren Malchow, and Larry Sushelnitski in the field collection of samples. Laboratory support was given by Scott Nelson, Washington State University. We are grateful for the technical assistance of staff at the Agri-Food Laboratories Branch, Alberta Agriculture and Rural Development. CANFAX is thanked for helping us randomly select participating feedlots for the study. Funding was provided by Alberta Livestock Industry Development Fund, Alberta Agricultural Research Institute, and Alberta Beef Producers.

Disclosure Statement

No competing financial interests exist.

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